Who we are
Faculty is an applied AI company that helps organisations who have the scale, data, and foresight to adopt AI into their business. We're helping make AI real across society by providing a unique combination of strategy, software and skills to our customers everything needed to successfully create value from AI. Founder-led and with over 80 PhDs, we're a team of specialists with experience across healthcare, finance, government, retail, engineering, construction and a host of other sectors.
We believe that AI should be trustworthy, impactful and beneficial across society. Those principles have shaped our work with more than 230 organisations across the public and private sectors as we help them use AI to act faster, make better decisions and understand more deeply. Thanks to our dedicated AI safety research programme, we're constantly refining our systems to make AI safer, more secure and more reliable.
As a data scientist, fundamentally your role is to help customers solve their problems using data science and AI; this involves applying a variety of techniques, ranging from simple data analysis to designing and implementing bespoke machine learning algorithms. We have previously worked on a multitude of different technical solutions for our clients, using Bayesian hierarchical modelling to develop an early warning system for the NHS during the COVID-19 pandemic, modelling 3D point cloud data to identify and measure assets for Network Rail, and using NLP to identify topics in market research. Prior knowledge of these techniques is not a prerequisite as we are looking for both experienced candidates and those who want to learn. We anticipate that with our support, you could become an expert in one of these areas even if you don't yet have much hands-on experience.
Additionally, your contribution won't be limited to your technical skills. Using practical and business sense, you will help our excellent commercial team build lasting relationships with our customers, shaping the direction of both current and future projects.
As we are a growing business, we need people who take initiative. You will take on more responsibility from day one than you would expect in comparable roles elsewhere, whilst in turn benefitting from the support and mentorship of our more seasoned team members. Data scientists at Faculty take pride in
- Solving problems with the best data-science techniques and the scientific method
- Communicating technical content at the right level both internally and to customers.
- Fostering a collaborative work environment, sharing knowledge, and bringing the best out of everyone in the team.
- Seeking out innovative ways to help Faculty grow, for example, by developing shared technical and non-technical resources.
Now for the practical part - to succeed in this role, you'll need
- At least 3 years of relevant experience; relevant experience includes quantitative academic research (e.g. STEM PhD), professional data-science positions, or a combination of the two.
- Programming experience as evidenced by earlier work in data science, academic research or software engineering. Although your programming language of choice (e.g. R, MATLAB or C) is not important, we do require the ability to become a fluent Python programmer in a short timeframe.
- The ability to reason mathematically and an understanding of common statistical tests and/or probability.
- Experience using common machine learning algorithms as evidenced by previous work or side projects, with the ability to think creatively when an innovative solution is necessary.
- Experience of manipulating data using the standard libraries for data science (e.g. NumPy, Pandas, Scikit-Learn or equivalents in other programming languages).
- An appreciation for the scientific method as applied to the commercial world; the ability to turn client requests into problems that can be solved using data science; resourcefulness in overcoming difficulties through creativity, commitment and collaboration; and an inquisitive and questioning mindset in evaluating the performance and impact of models upon deployment.
- An interest in working alongside our customers and to learn about the commercial aspects of the job.
- Effective verbal and written communication - you should be comfortable with presenting your work in front of customers.
- The ability to follow a project plan and stick to deadlines, as well as proactively solve problems that emerge.
The following would be a bonus, but are by no means required
- Prior commercial experience, particularly if this involved customer-facing work or project management.
- Research experience (PhD or Postdoc) as evidenced by academic publications and conference talks.
- Working knowledge of any of following ML domains NLP, Bayesian inference, computer vision, deep learning, causal modelling, AI safety
- Experience creating web apps using e.g. Dash, Flask, React.js
- Familiarity with MLOps including deployment, monitoring and scalability tooling.
- Unlimited holidays We encourage each other to use this time to take a break, work on personal projects, or to spend time with their friends and family.
- Genuinely flexible working We believe people have needs, responsibilities and interests that require something different to a strict 9-6 working day. We trust people to organise and take accountability for their own work and do our best to support their lives outside Faculty.
- Sanctus mental health coaching We offer access to confidential coaching sessions with mental healthcare professionals from Sanctus to ensure we offer the opportunity for our employees the chance to discuss and maintain their mental health.
- Parental Leave We offer a progressive, equal, and generous parental leave policy.All parents are given 15 weeks leave at full pay in addition to statutory time off.
- Cycle to work scheme for all employees.
- Access to TechScheme monthly personal tech repayment process.
- £100 Work from Home equipment fund for any work-essential tech or home office equipment (on top of your laptop, of course).
- Breakfast and more fruit, drinks and snacks than you could ever eat provided (for office-based employees).
- Yoga sessions twice a week.
It takes all sorts to make AI real
We know that we can't make AI real if our people don't reflect the real diversity of society. More importantly, discrimination of any kind doesn't align with our ethics. With that in mind, we welcome applications from all ages, genders, identities, races, ethnicities, sexual orientations, and backgrounds.
We also know that equality and inclusion go beyond the hiring process, so we work hard to make Faculty a comfortable, safe and supportive environment for everyone.